Fortinet's new firewall uses machine learning to detect threats

In the latest version of its web application firewall, American cybersecurity firm Fortinet has introduced machine learning capabilities to detect behaviour-based threats in web applications, a report in The Economic Times stated.

The new FortiWeb iteration can detect threats more accurately, allowing for faster response times for automated blocking, the report added.

As web applications become increasingly susceptible to cyberattacks, enterprises are using WAFs to protect their data.

Traditional WAFs relied on application learning (AL) to detect threats but these have become time-consuming to manage and have proven to be limited, the ET report said.

While AL uses a single layer to detect anomalies, machine learning uses a two-layered approach, the report added.

The new FortiWeb can also be seamlessly integrated with third-party services to provide advanced protection while scanning web application attachments.

FortiWeb is available for use in hardware applications, virtual machines, cloud platforms like Amazon’s AWS and Microsoft’s Azure, and it can also be hosted as a cloud solution, the ET report stated.